Example-first conditions outperformed problem-first conditions on an immediate circuit test¶

Claim · All claims
Evidence · 1 study · causal r? · q3 · n=96
Currency · newest study 2011 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? In this novice circuit experiment, WE and WE–PS outperformed PS and PS–WE on the immediate test and had lower reported training effort. Neither within-pair contrast was detected; equivalence was not tested.

q3 i? Sequences that begin with a worked example (examples only, or example–problem pairs) produce lower invested mental effort than problems only for novices; problem–example pairs do not. → van Gog et al. 2011

q3 i? Sequences that begin with a worked example produce higher test performance than problems only for novices; problem–example pairs do not outperform problems only. → van Gog et al. 2011

Evidence¶

van Gog et al. 2011¶

van Gog, T., Kester, L., & Paas, F. (2011). Effects of worked examples, example-problem, and problem-example pairs on novices' learning. Contemporary Educational Psychology, 36(3), 212–218. doi:10.1016/j.cedpsych.2010.10.004

q3 · peer-reviewed experiment · i? · omnibus partial η² only; no pairwise standardized effect · n=96 · causal · r?

Peer-reviewed author manuscript, Methods/Results and Table 1, manuscript pp. 10–16, 26. doi:10.1016/j.cedpsych.2010.10.004. Full method/result verification by the editing agent; not independent human verification.

103 Dutch secondary students were randomized within sessions; 96 were analyzed. Seven missing-test exclusions occurred in PS (4) and WE–PS (3). Prior knowledge was a covariate. Four paper tasks varied example/problem format; calculators and formula sheets were allowed, previous solutions unavailable. Two same-session test problems varied surface details or fault complexity; total score range was 0–8. One author scored blind to condition. Effort was self-reported on a nine-point scale.

Test ANCOVA: F(3,91)=9.00, partial η²=.23; training effort: F(3,91)=7.78, partial η²=.20. Bonferroni contrasts supported the stated ordering. These are omnibus effects, not pairwise standardized gains or individual probabilities. Randomization does not ensure exact baseline equivalence; differential exclusions and narrow, instruction-aligned tests constrain interpretation.

Studies bearing on this claim¶

Should the example come before or after the practice problem? This table gathers the studies behind this claim and the 2 narrower claims that bear on it: 2 distinct studies (1 causal, 1 review), q2–q3, 0 of 2 with an effect size coded. One row per study, codes as each entry records them; no effect is averaged and no verdict is drawn. Built by scripts/synthesize_claim.py from eval/synthesis/; a row that looks wrong is fixed on the claim it comes from.

Discussion¶

The comparison supports a bounded example-first choice for similar initial tasks. It does not test an adaptive fading policy, a mandatory alternation rule, delayed retention, live repair safety or open-ended creativity. Mental effort is an observed report; schema acquisition is an explanation, not a direct measurement. No learner-valued goal mechanism was measured.

Do not conflate example→problem pairs with completion problems: the latter omit solution steps within a task. Do not substitute this study's task count, timing or test threshold as universal requirements. A short diagnostic attempt before instruction is also distinct from a sustained problem-first learning design.

Merged from “Example-problem sequences reduce cognitive load and improve learning outcomes.” (example-problem-sequences-reduce-cognitive-load): This page combines two earlier pages on the same claim, worked-examples-example-problem-sequences and example-problem-sequences-reduce-cognitive-load-and-improve-learning-outcomes, which now resolve to it as aliases.

Merged from “Example–problem sequences reduce cognitive load and improve learning outcomes” (example-problem-sequences-reduce-cognitive-load-and-improve-learning-outcomes): Mechanism. The claim sits within Cognitive Load Theory: problem-only practice forces novices to search solution paths, consuming working memory that could otherwise build schemas. Studying worked examples first or interleaved with problems offloads that search, consistent with the broader finding that cognitive load reduction improves learning and that chunking reduces working memory load.

Expertise reversal. The benefit of examples diminishes as learner expertise grows; for advanced learners, example-based sequences can become redundant or counterproductive — see the expertise reversal effect and Worked examples can become redundant or counterproductive for advanced learners.. Designers should fade examples and shift toward independent problem-solving as competence develops.

Sequencing questions. In van Gog 2011, the two example-first conditions outperformed both problem-first conditions on the immediate test. The study did not detect a difference between examples only and example–problem pairs, or between problems only and problem–example pairs. The best ratio, spacing, and delayed effect remain open design questions.

Relation to fading and completion problems. Sequencing is closely related to fading strategies in which worked steps are progressively replaced by problem-solving steps — see Example-based sequences outperform problem-only practice for novices, and fading support is argued to aid transfer. Alternating full examples with full problems is the coarsest form of this; faded examples are a finer-grained variant.

Single-study limitation. Both subclaims currently rest on one experiment with 96 analyzed participants in electrical-circuits troubleshooting. Replication in other domains and with larger samples would strengthen confidence; do not generalize this ordering contrast to delayed or far-transfer outcomes without further evidence.

Related Claims¶

• In one experiment with 256 undergraduates, computer-based lesson versions that included practice produced significantly higher posttest scores than versions without practice — the general claim this finding bears on, with the studies behind it

• Minimal guidance is less effective for novices than explicit instruction — the general claim this finding bears on, with the studies behind it

• Fading support promotes the transfer of responsibility from instructor to learner. — the general claim this finding bears on, with the studies behind it

• Example-based sequences outperform problem-only practice for novices, and fading support is argued to aid transfer — the general claim this finding bears on, with the studies behind it

• Identical pairs qualify an example-first final-test advantage

• Fading and principle prompts in probability learning
• PS-I fosters learning only if specific design features (contrasting cases or building instruction on student solutions) are implemented — reports the opposite
• Instructional guidance that helps novices can become redundant or counterproductive as expertise grows. — the general claim this finding bears on, with the studies behind it
• Worked examples reduce unnecessary search for novices.
• CLT-aligned e-learning modules improved cognitive load profiles and OSCE performance in simulation-based medical training (review-attributed to Gutierrez et al., 2023) — related
• Worked examples can become redundant or counterproductive for advanced learners. — expertise reversal effect
• Studying worked examples improves novices' algebra performance on problems with the same structure as the examples — worked examples improve math performance (meta-analysis)
• Cognitive load reduction improves learning — the general mechanism this claim instantiates.
• Chunking reduces working memory load — a complementary load-reduction technique.
• Expertise reversal effect — the underlying theory explaining when example-based sequencing loses its benefit.
• Productive Failure Improves Conceptual Learning — related
• Alternating example-practice pairs produce faster and more accurate near-transfer solutions than blocked presentation of examples followed by practice — related
• Example–problem pairs and examples-only are more effective than problem–example pairs for novices, with no significant difference between the first two — possibly the same claim (merge candidate)
• Sequence of worked examples and problems had no significant effect on self-reported cognitive load, but higher prior knowledge was associated with lower load in experimental design — related
• Task sequence effects on mental effort reverse between learning phase and transfer test — related
• Example–problem pairs are more efficient than problem–example pairs for both gifted and nongifted primary school students — a narrower finding that bears on this claim
• Order of worked examples and problem solving had no significant effect on application and transfer scores in experimental design or graphing — related
• The relationship between learners' prior knowledge and the optimal instructional sequence may not be straightforward — reports the opposite
• For introductory biology students with low topic-specific prior knowledge, problem-solving-first (PS-I) outperformed instruction-first (I-PS) on a near-transfer test — related
• Studying worked examples is more effective and more efficient than problem solving for novice learners (the worked example effect) — related
• Solving practice problems invested less mental effort than contrasting or erroneous examples, contrary to the worked-example-effect hypothesis — related
• Presenting primary knowledge first and then secondary knowledge was more efficient in both performance and motivation — related
• Restudy of worked examples invested much less mental effort than testing after four examples, but this difference was not replicated with vocational students — related
• Completing steps in partially worked-out examples leads students to underestimate their test performance and report higher mental effort than studying fully worked examples — related
• Problem-solving facilitates diagnostic competences independent of learners' professional knowledge base — related